FEW SHOT PHOTOGRAMETRY: A COMPARISON BETWEEN NERF AND MVS-SFM FOR THE DOCUMENTATION OF CULTURAL HERITAGE

Abstract

Abstract. 3D documentation methods for Digital Cultural Heritage (DCH) domain is a field that becomes increasingly interdisciplinary, breaking down boundaries that have long separated experts from different domains. In the past, there has been an ambiguous claim for ownership of skills, methodologies, and expertise in the heritage sciences. This study aims to contribute to the dialogue between these different disciplines by presenting a novel approach for 3D documentation of an ancient statue. The method combines TLS acquisition and MVS pipeline using images from a DJI Mavic 2 drone. Additionally, the study compares the accuracy and final product of the Deep Points (DP) and Neural Radiance Fields (NeRF) methods, using the TLS acquisition as validation ground truth. Firstly, a TLS acquisition was performed on an ancient statue using a Faro Focus 2 scanner. Next, a multi-view stereo (MVS) pipeline was adopted using 2D images captured by a Mini-2 DJI Mavic 2 drone from a distance of approximately 1 meter around the statue. Finally, the same images were used to train and run the NeRF network after being reduced by 90%. The main contribution of this paper is to improve our understanding of this method and compare the accuracy and final product of two different approaches - direct projection (DP) and NeRF - by exploiting a TLS acquisition as the validation ground truth. Results show that the NeRF approach outperforms DP in terms of accuracy and produces a more realistic final product. This paper has important implications for the field of CH preservation, as it offers a new and effective method for generating 3D models of ancient statues. This technology can help to document and preserve important cultural artifacts for future generations, while also providing new insights into the history and culture of different civilizations. Overall, the results of this study demonstrate the potential of combining TLS and NeRF for generating accurate and realistic 3D models of ancient statues.